Identifying hybrid heating systems in the residential sector from smart meter data

In this paper, we identify hybrid heating systems on a single residential customer’s premises using smart meter data. A comprehensive methodology is developed at a generic level for residential sector buildings to identify the type of primary and support heating systems. The methodology includes the use of unsupervised and supervised learning algorithms both separately and combined. It is applied to two datasets that vary in size, quality of data, and availability and reliability of background information. The datasets contain hourly electricity consumption profiles of residential customers together with the outdoor temperature. The validation metrics for the developed algorithms are elaborated to provide a probabilistic evaluation of the model. The results show that it is possible to identify the types of both primary and support heating systems in the form of probability of having electric- or non-electric type of heating. The results obtained help estimate the flexibility domain of the residential building sector and thereby generate a high value for the energy system as a whole

A study on the deregulation of the Finnish electricity markets

Abstract Governments have regarded the electricity industry as a leading industrial sector throughout the history. Because of its strategic importance to industrial development, its impacts on the social and environmental issues and its natural monopoly characteristics, it has been seen necessary to regulate electricity industry effectively. However, in the mid 1980s it was realised that even though transmission and distribution networks are natural monopolies, the scale economies in electricity production at the generating unit level had exhausted at a unit size of about 500 MW. This meant that supply and generation had become potentially competitive activities. In Finland the new Electricity Market Act (EMA) came into force in 1.11.1995. According to it the production and supply of electricity became deregulated and competition was introduced to the industry. The main aim of the law was to improve efficiency. This dissertation analyses, both theoretically and empirically, the impacts of deregulation to the Finnish electricity markets. In chapter two we discuss on the grounds and incentives of the deregulation processes that have been carried out in different countries. We also determine the crucial factors in order succeed in the deregulation process. According to our view the success depend on the number of active players in the wholesale market, the rules of the bidding procedure, the organisation of the demand side operation, the neutrality of transmission grid, the structure of production technologies and the ownership structure of the industry. In chapter three we theoretically model the profit maximising behaviour of the Finnish electricity companies based on different stages of vertical integration and on different stage of competition. According to our results the profit maximising pricing rules of distribution units is dependent on the stage of integration and on the stage of competition. The separated distribution company maximises profits by setting the distribution price equal to the long-run marginal costs plus mark-up determined by price elasticity of demand. The integrated distribution unit has to take also the impacts on the supply unit into account when setting the distribution price. Chapter four considers the consequences of deregulation to the wholesale price of electricity and the market structure of the industry. It is interesting to question whether deregulation in some circumstances may lead to higher prices instead of lower ones. The relationship between the Cournot equilibrium on the one hand and Bertrand equilibrium on the other will be quantitatively explored. The results indicate that deregulation can result in a significant price increase and output decrease in Finland if there occurs Cournot type of competition. In chapter five we consider alternative pricing policies for a regulated distribution company and empirically analyse is it possible to achieve welfare improvements by changing the prevalent price structure to the more efficient one. We use four different pricing methods which are marginal cost pricing, fully distributed cost pricing (FDC), Ramsey pricing and optimal two-part tariffs. The results indicate that it is possible to improve welfare quite markedly by switching from the existing pricing principles to more efficient ones. The resulting welfare is highest if we use the first best prices based on marginal costs or optimal two-part tariffs

Comparing welfare effects of different regulation schemes: an application to the electricity distribution industry

Abstract We compare the welfare effects of different regulation schemes of electricity distribution utilities. The regulation schemes are price cap regulation, cost of service regulation, menu of cost-contingent contracts and simple menus of contracts. In our calculations we utilize the benchmarking information of firm specific costs. The firm specific cost information of Finnish electricity distribution utilities is obtained by using various Stochastic Frontier models. Our basic result is that welfare can be improved by changing the cost of service regulation scheme to the menu of contracts regulation. Welfare also increases in the case of price cap regulation. There is however, a significant difference among regulation regimes on how this improved welfare is distributed to consumers and producers

Observed and unobserved heterogeneity in stochastic frontier models

Abstract Stochastic frontier modeling has proceeded rapidly recently. Heterogeneity modeling internalized into frontier estimation has opened up new promising possibilities. In this paper we study different ways of considering heterogeneity in stochastic frontier models. It is possible to take heterogeneity into account by including those effects in the mean and/or variance of the distribution of inefficiency (observed heterogeneity) or by randomizing some parameters of the stochastic frontier model (unobserved heterogeneity). We compare the advantages of heterogeneity including models over the conventional random effects models for measuring the cost efficiency of electricity distribution utilities. Our results indicate that in all heterogeneity accounting models mean inefficiency decreases significantly compared to the basic random effects model. According to our results randomizing some of the parameters seems to help to capture the unobserved heterogeneity and hence this kind of firm specific heterogeneity does not appear as inefficiency in our estimation results. Notable is that the model which accounts observed heterogeneity and the models which account unobserved heterogeneity produce clearly different rank orders

Carbon footprint at institutions of higher education:the case of the University of Oulu

Abstract As an answer to the need to reduce greenhouse gas emissions, organizations are increasingly making efforts to account for their carbon footprint. While general guidelines for carbon footprint calculation exist, they usually do not consider special characteristics of organisations such as institutions of higher education. Case studies can act then as learning tools, and comparisons between applied methodologies can be used to develop best practices. However, a lack of case studies published in peerreviewed journals limits access to the calculation results. This work provides a case study for a Northern European institution to extend the pool of available calculation methodologies tested under real-life conditions. The carbon footprint calculation of the University of Oulu utilises a hybrid model, combining approaches of Environmentally Extended Input-Output Analysis and Life-Cycle Assessment. The focus of the work was to consider included scopes and categories of emissions that represent indirect and non-energy-related greenhouse gas emissions, such as commuting or procurement of research and laboratory equipment. In 2019, the institution’s emission inventory sums up to 19,072 t CO2e, with the highest share due to the use of district heat on campus. Another goal of conducting this research was to show the limitations researchers might encounter when analysing caused emissions on an organisational level, and how the calculated carbon footprint can help to identify the best mitigation measures and possibilities for universities to reach carbon neutrality. It was found that the availability of information and missing strategies for data collection are prominent limiting factors. Favourable mitigation measures include the implementation of energysaving policies and improved policies for procurements